AWS Storage Blog
Category: Edge
Bring Amazon S3 closer to the edge with Nasuni
Customers in Manufacturing, Real Estate, Engineering and Construction, Healthcare and other related industries often have remote facilities with limited network bandwidth where large amounts of data generated at the edge needs to be stored, processed and analyzed for making decisions in real time. For example, applications running in manufacturing plants need low latency access to […]
Optimizing cost with long-term pricing options for AWS Snowball
At the edge, in austere, non-data center environments, and in locations where there’s lack of consistent network connectivity, optimizing costs and operations is essential to successful outcomes. It can be difficult to manage costs and achieve goals in these austere environments, with limited resources and capabilities. The Snow Family, comprised of AWS Snowcone and AWS Snowball, enable you to […]
Autonomous vehicle data collection with AWS Snowcone and AWS IoT Greengrass
Self-driving and self-flying vehicles — autonomous cars, airplanes, and drones — require vast amounts of data to fulfill their promise of a safe mode of transportation for goods and people. Connected vehicles and the Internet of Things (IoT) have a strong influence on the way we collect and process low-bandwidth telemetry data, in addition to […]
Making it even simpler to create and manage your AWS Snow Family jobs
Customers use AWS Snow Family devices to run storage, compute, and data-processing operations in austere environments with inconsistent (or no) network connectivity. The AWS Snow Family, comprised of AWS Snowcone and AWS Snowball, offers a number of physical devices and capacity points, most with built-in computing capabilities. These devices help physically transport up to exabytes […]
Implementing sensor workflows using AWS Snowcone and AWS IoT Greengrass
In our first blog of this series, we covered using an IoT device to store the sensor data on an Amazon EC2 instance running on AWS Snowcone. That use case covered collecting data from sensors in locations such as a factory floor or a mine with austere network connectivity. There are other instances where you […]
Video transcoding at the edge with AWS Snowcone
A customer doing video analysis in remote locations has the following problem: they must capture high-resolution video in the field and then transfer that data to a durable, highly available data store in the cloud for long-term storage. They also want to keep copies of video files in the remote location so that they can […]
AWS re:Invent recap: Edge computing innovation with the AWS Snow Family
Ramesh Kumar, Senior Product Manager of the AWS Snow Family, just broadcasted his AWS re:Invent 2020-2021 session yesterday: “Edge computing innovation with AWS Snowcone and AWS Snowball Edge.” You can now watch Ramesh’s 30-minute edge session on-demand. In this blog, I discuss highlights from Ramesh’s session, including an overview of AWS services from the cloud […]
Running Kubernetes cluster with Amazon EKS Distro across AWS Snowball Edge
AWS Snowball Edge customers are running applications for edge local data processing, analysis, and machine learning using Amazon EC2 compute instances on Snowball Edge devices in remote or disconnected locations. Customers use Snowball Edge devices in locations including, but not limited to, cruise ships, oil rigs, and factory floors with no or limited network connectivity. […]
Best practices for accelerating data migrations using AWS Snowball Edge
Customers frequently perform bulk migrations of their application data when moving to the cloud. There are different online and offline methods for moving your data to the cloud. When proceeding with a data migration, data owners must consider the amount of data, transfer time, frequency, bandwidth, network costs, and security concerns. No matter how data […]
Building an IoT solution at the edge with AWS Snowcone
UPDATE: The second blog post in this two-post series was published on January 5, 2020. Internet of Things (IoT) applications, like other applications, require edge solutions to operate in austere conditions with limited network connectivity or limited infrastructure. IoT applications at the edge can span numerous uses, like automation, optimization, and intelligent manufacturing to name […]